露天矿山道路运输系统优化问题是矿山复杂大系统协同优化的重要组成部分，对于降低矿山生产运营成本、提高矿山生产及组织效率具有极为重要的现实意义。但近年来，随着我国露天矿山建设质量的标准化，产量规模、作业设备的逐步大型化，部分矿山运输系统的瓶颈问题开始凸显，特别是以静态道路网络分析方法为基础的传统路径优化规划模型及算法，当面临更加复杂、多变的调度决策任务时，部分规划模型及算法易受到基础能耗目标建模限制，很难给出全局现实最优解。为有效解决传统模型评价建模困难、寻径效率受限等问题，以神华新疆公司红沙泉露天煤矿为例，在时变运输功描述系统全局能耗波动效应的理论基础上，尝试融合车-路耦合思想，提出兼顾路面随机损伤作用下的费用评价函数及路径规划模型，并结合该矿道路阻力系数的隶属度函数模型给出了全局费用评价函数的合理估计；为进一步提高规划模型求解效率，提出采用快速搜索随机树算法(Rapidly exploring Random Tree，RRT)构建路径拓扑连通性的启发式策略的基本方法，并配合遗传算法对路径规划模型进行求解，实现了路径几何拓扑连通性与标量目标值约束解耦的同时，完成了对露天矿复杂路径条件下寻径问题的快速求解。经多组仿真实验验证，所述算法能快速收敛于全局最优解，经对比试验论证，所述方法及策略对于解决露天矿山路径规划优化问题可行且有效。所述方法为后续基于路面波动作用下的运输系统成本分析及评价提供了研究方向及基础，为融合交叉学科分析露天矿山复杂大系统的决策问题贡献了全新的体系方法。

The optimization of road transportation system in open pit mines is an important part of the optimization of complex large system in open pit mines. It is of great practical significance to reduce the production and operation cost and improve the production and organizational efficiency of mines. But in recent years, with open pit mine quality standardization construction in China, the scale of production and operation equipment and enlarged gradually, part of the mine transport system bottleneck problem began to highlight, especially on the basis of the static road network analysis method of the traditional routing optimization planning models and algorithms. When faced with more complex and variable scheduling decisions, some programming models and algorithms are easily limited by the modeling of the basic energy consumption target, and it is difficult to give the global realistic optimal solution. To effectively solve the traditional model of evaluation modeling difficulties, such as the limited efficiency for size problem, this article with Shenhua Xinjiang company Hongshaquan open pit coal mine as an example, On the basis of describing the fluctuating effect of global energy consumption of the time-varying transport power system and combining the vehicle-road coupling idea, the cost evaluation function and routing planning model under the effect of random road damage are proposed, and the reasonable estimation of the global cost evaluation function is given by combining the membership function model of road resistance coefficient of this mine. In order to further improve the efficiency of programming model, puts forward a quick search Random Tree algorithm (Rapidly-exploring the Random Tree, RRT) build path topology connectivity and the basic methods of heuristic strategies, and cooperate with the genetic algorithm is used for path planning model, realized the path geometry topology connectivity and scalar target constraint decoupling, and the fast solution of path finding problem in open pit mine under complex path condition is completed. The simulation results show that the algo-rithm can converge to the global optimal solution rapidly, and the comparison test proves that the method and strategy are feasible and effective for solving the optimization problem of open pit mine routing planning. The method described in this paper provides a research direction and basis for the subsequent cost analysis and evaluation of transportation system under the action of road surface fluctuation, and contributes a brand-new system method for the analysis of decision-making problems of complex large-scale system in open-pit mines by inte-grating cross-disciplines.

1 RRT算法基本原理

2 露天矿山路径优化问题建模

   2.1 模型的参、变量定义

   2.2 约束条件

   2.3 目标函数

   2.4 模型中的波动参数估计

3 基于改进RRT的路径优化算法

   3.1 基于改进RRT算法的启发式策略

   3.2 融合启发式策略的寻径算法设计

4 仿真实验对比分析

5 结论